440 citations · 1.6k across the 34 of their papers we have counts for
3 papers · 1 filter
CrossSplit: Mitigating Label Noise Memorization through Data Splitting
Jihye Kim, Aristide Baratin, Yan Zhang +1
We approach the problem of improving robustness of deep learning algorithms in the presence of label noise. Building upon existing label correction and co-teaching methods, we prop…
Lazy vs hasty: linearization in deep networks impacts learning schedule based on example difficulty
Thomas George, Guillaume Lajoie, Aristide Baratin
Among attempts at giving a theoretical account of the success of deep neural networks, a recent line of work has identified a so-called lazy training regime in which the network ca…
Using Representation Expressiveness and Learnability to Evaluate Self-Supervised Learning Methods
Yuchen Lu, Zhen Liu, Aristide Baratin +3
We address the problem of evaluating the quality of self-supervised learning (SSL) models without access to supervised labels, while being agnostic to the architecture, learning al…